Tag Archives: EPFL (Ecole polytechnique fédérale de Lausanne)

Reversing lower limb paralysis

This regenerative treatment is at a very early stage, which means the Swiss researchers have tried it on mice as you can see in the following video (runtime: 2 mins. 15 secs.). Towards the end of the video, researcher Grégoire Courtine cautions there are many hurdles before this could be used in humans, if ever,

A September 22, 2023 Ecole Polytechnique Fédérale de Lausanne (EPFL) press release (also on EurekAlert but published September 21, 2023) by Emmanuel Barraud, describes the work in more detail,

When the spinal cords of mice and humans are partially damaged, the initial paralysis is followed by the extensive, spontaneous recovery of motor function. However, after a complete spinal cord injury, this natural repair of the spinal cord doesn’t occur and there is no recovery. Meaningful recovery after severe injuries requires strategies that promote the regeneration of nerve fibers, but the requisite conditions for these strategies to successfully restore motor function have remained elusive.

“Five years ago, we demonstrated that nerve fibers can be regenerated across anatomically complete spinal cord injuries,” says Mark Anderson, a senior author of the study. “But we also realized this wasn’t enough to restore motor function, as the new fibers failed to connect to the right places on the other side of the lesion.” Anderson is the director of Central Nervous System Regeneration at .NeuroRestore and a scientist at the Wyss Center for Bio and Neuroengineering.

Working in tandem with peers at UCLA [University of California at Los Angeles] and Harvard Medical School, the scientists used state-of-the-art equipment at EPFL’s Campus Biotech facilities in Geneva to run in-depth analyses and identity which type of neuron is involved in natural spinal-cord repair after partial spinal cord injury. “Our observations using single-cell nuclear RNA sequencing not only exposed the specific axons that must regenerate, but also revealed that these axons must reconnect to their natural targets to restore motor function,” says Jordan Squair, the study’s first author. The team’s findings appear in the 22 September 2023 issue of Science.

Towards a combination of approaches

Their discovery informed the design of a multipronged gene therapy. The scientists activated growth programs in the identified neurons in mice to regenerate their nerve fibers, upregulated specific proteins to support the neurons’ growth through the lesion core, and administered guidance molecules to attract the regenerating nerve fibers to their natural targets below the injury. “We were inspired by nature when we designed a therapeutic strategy that replicates the spinal-cord repair mechanisms occurring spontaneously after partial injuries,” says Squair.

Mice with anatomically complete spinal cord injuries regained the ability to walk, exhibiting gait patterns that resembled those quantified in mice that resumed walking naturally after partial injuries. This observation revealed a previously unknown condition for regenerative therapies to be successful in restoring motor function after neurotrauma. “We expect that our gene therapy will act synergistically with our other procedures involving electrical stimulation of the spinal cord,” says Grégoire Courtine, a senior author of the study who also heads .NeuroRestore together with Jocelyne Bloch. “We believe a complete solution for treating spinal cord injury will require both approaches – gene therapy to regrow relevant nerve fibers, and spinal stimulation to maximize the ability of both these fibers and the spinal cord below the injury to produce movement.”

While many obstacles must still be overcome before this gene therapy can be applied in humans, the scientists have taken the first steps towards developing the technology necessary to achieve this feat in the years to come.

Here’s a link to and a citation for the paper,

Recovery of walking after paralysis by regenerating characterized neurons to their natural target region by Jordan W. Squair, Marco Milano, Alexandra de Coucy, Matthieu Gautier, Michael A. Skinnider, Nicholas D. James, Newton Cho, Anna Lasne, Claudia Kathe,Thomas H. Hutson, Steven Ceto, Laetitia Baud, Katia Galan, Viviana Aureli, Achilleas Laskaratos, Quentin Barraud, Timothy J. Deming, Richie E. Kohman, Bernard L. Schneider, Zhigang He, Jocelyne Bloch, Michael V. Sofroniew, Gregoire Courtine, and Mark A. Anderson. Science 21 Sep 2023 Vol 381, Issue 6664 pp. 1338-1345 DOI: 10.1126/science.adi641

This paper is behind a paywall.

This March 25, 2015 posting, “Spinal cords, brains, implants, and remote control,” features some research from EPFL researchers whose names you might recognize from this posting’s research paper.

Mentioned in the press release, the Swiss research centre website for NeuroRestore is here.

D-Wave Systems demonstrates quantum advantage on optimization problems with a 5,000-qubit programmable spin glass

This May 17, 2023 article by Ingrid Fadelli for phys.org describes quantum research performed by D-Wave Systems (a company in Vancouver, Canada) and Boston University (Massachusetts, US), Note: Links have been removed,

Over the past decades, researchers and companies worldwide have been trying to develop increasingly advanced quantum computers. The key objective of their efforts is to create systems that will outperform classical computers on specific tasks, which is also known as realizing “quantum advantage.”

A research team at D-Wave Inc., a quantum computing company, recently created a new quantum computing system that outperforms classical computing systems on optimization problems. This system, introduced in a paper in Nature, is based on a programmable spin glass with 5,000 qubits (the quantum equivalents of bits in classical computing).

“This work validates the original hypothesis behind quantum annealing, coming full circle from some seminal experiments conducted in the 1990s,” Andrew D. King, one of the researchers who carried out the study, told Phys.org.

“These original experiments took chunks of spin-glass alloy and subjected them to varying magnetic fields, and the observations suggested that if we made a programmable quantum spin glass, it could drive down to low-energy states of optimization problems faster than analogous classical algorithms. A Science paper published in 2014 tried to verify this on a D-Wave Two processor, but no speedup was found.”

“This is a ‘full circle’ moment, in the sense that we have verified and extended the hypothesis of the UChicago [University of Chicago] and NEC [Nippon Electric Company] researchers; quantum annealing shows a scaling advantage over simulated thermal annealing,” King said. “Ours is the largest programmable quantum simulation ever performed; reproducing it classically is way beyond the reach of known methods.”

“We have a clear view of quantum effects and very clear evidence, both theoretical and experimental, that the quantum effects are conferring a computational scaling advantage over classical methods,” King said. “We want to highlight the difference between this original definition of quantum advantage and the fact that it is sometimes used as a stand-in term for quantum supremacy, which we have not demonstrated. [emphases mine] Gate-model quantum computers have not shown any capabilities approaching this for optimization, and I personally don’t believe they ever will.”

“For a long time, it was subject for debate whether or not coherent quantum dynamics were playing any role at all in quantum annealing,” King said. “While this controversy has been rebuked by previous works, this new research is the clearest demonstration yet, by far.”

An April 19, 2023 D-Wave Systems news release, which seems to have been the basis for Fadelli’s article, provides more detail in a release that functions as a research announcement and a sales tool, Note: Links have been removed,

D-Wave Quantum Inc. (NYSE: QBTS), a leader in quantum computing systems, software, and services—and the only provider building both annealing and gate-model quantum computers, today published a peer-reviewed milestone paper showing the performance of its 5,000 qubit Advantage™ quantum computer is significantly faster than classical compute on 3D spin glass optimization problems, an intractable class of optimization problems. This paper also represents the largest programmable quantum simulation reported to date.

The paper—a collaboration between scientists from D-Wave and Boston University—entitled “Quantum critical dynamics in a 5,000-qubit programmable spin glass,” was published in the peer-reviewed journal Nature today and is available here. Building upon research conducted on up to 2,000 qubits last September, the study shows that the D-Wave quantum processor can compute coherent quantum dynamics in large-scale optimization problems. This work was done using D-Wave’s commercial-grade annealing-based quantum computer, which is accessible for customers to use today.

With immediate implications to optimization, the findings show that coherent quantum annealing can improve solution quality faster than classical algorithms. The observed speedup matches the theory of coherent quantum annealing and shows​ a direct connection between coherence and the core computational power of quantum annealing.

“This research marks a significant achievement for quantum technology, as it demonstrates a computational advantage over classical approaches for an intractable class of optimization problems,” said Dr. Alan Baratz, CEO of D-Wave. “For those seeking evidence of quantum annealing’s unrivaled performance, this work offers definitive proof.

This work supports D-Wave’s ongoing commitment to relentless scientific innovation and product delivery, as the company continues development on its future annealing and gate model quantum computers. To date, D-Wave has brought to market five generations of quantum computers and launched an experimental prototype of its sixth-generation machine, the Advantage2™ system, in June 2022. The full Advantage2 system is expected to feature 7,000+ qubits, 20-way connectivity and higher coherence to solve even larger and more complex problems. Read more about the research in our Medium post here.

Paper’s Authors and Leading Industry Voices Echo Support

“This is an important advance in the study of quantum phase transitions on quantum annealers. It heralds a revolution in experimental many-body physics and bodes well for practical applications of quantum computing,” said Wojciech Zurek, theoretical physicist at Los Alamos National Laboratory and leading authority on quantum theory. Dr. Zurek is widely renowned for his groundbreaking contribution to our understanding of the early universe as well as condensed matter systems through the discovery of the celebrated Kibble-Zurek mechanism. This mechanism underpins the physics behind the experiment reported in this paper. “The same hardware that has already provided useful experimental proving ground for quantum critical dynamics can be also employed to seek low-energy states that assist in finding solutions to optimization problems.”

“Disordered magnets, such as spin glasses, have long functioned as model systems for testing solvers of complex optimization problems,” said Gabriel Aeppli, professor of physics at ETH Zürich and EPF Lausanne, and head of the Photon Science Division of the Paul Scherrer Institut. Professor Aeppli coauthored the first experimental paper demonstrating advantage of quantum annealing over thermal annealing in reaching ground state of disordered magnets. “This paper gives evidence that the quantum dynamics of a dedicated hardware platform are faster than for known classical algorithms to find the preferred, lowest energy state of a spin glass, and so promises to continue to fuel the further development of quantum annealers for dealing with practical problems.”

“As a physicist who has built my career on computer simulations of quantum systems, it has been amazing to experience first-hand the transformative capabilities of quantum annealing devices,” said Anders Sandvik, professor of physics at Boston University and a coauthor of the paper. “This paper already demonstrates complex quantum dynamics on a scale beyond any classical simulation method, and I’m very excited about the expected enhanced performance of future devices. I believe we are now entering an era when quantum annealing becomes an essential tool for research on complex systems.”

“This work marks a major step towards large-scale quantum simulations of complex materials,” said Hidetoshi Nishimori, Professor, Institute of Innovative Research, Tokyo Institute of Technology and one of the original inventors of quantum annealing. “We can now expect novel physical phenomena to be revealed by quantum simulations using quantum annealing, ultimately leading to the design of materials of significant societal value.”

“This represents some of the most important experimental work ever performed in quantum optimization,” said Dr. Andrew King, director of performance research at D-Wave. “We’ve demonstrated a speedup over simulated annealing, in strong agreement with theory, providing high-quality solutions for large-scale problems. This work shows clear evidence of quantum dynamics in optimization, which we believe paves the way for even more complex problem-solving using quantum annealing in the future. The work exhibits a programmable realization of lab experiments that originally motivated quantum annealing 25 years ago.”

“Not only is this the largest demonstration of quantum simulation to date, but it also provides the first experimental evidence, backed by theory, that coherent quantum dynamics can accelerate the attainment of better solutions in quantum annealing,” said Mohammad Amin, fellow, quantum algorithms and systems, at D-Wave. “The observed speedup can be attributed to complex critical dynamics during quantum phase transition, which cannot be replicated by classical annealing algorithms, and the agreement between theory and experiment is remarkable. We believe these findings have significant implications for quantum optimization, with practical applications in addressing real-world problems.”

About D-Wave Quantum Inc.

D-Wave is a leader in the development and delivery of quantum computing systems, software, and services, and is the world’s first commercial supplier of quantum computers—and the only company building both annealing quantum computers and gate-model quantum computers. Our mission is to unlock the power of quantum computing today to benefit business and society. We do this by delivering customer value with practical quantum applications for problems as diverse as logistics, artificial intelligence, materials sciences, drug discovery, scheduling, cybersecurity, fault detection, and financial modeling. D-Wave’s technology is being used by some of the world’s most advanced organizations, including Volkswagen, Mastercard, Deloitte, Davidson Technologies, ArcelorMittal, Siemens Healthineers, Unisys, NEC Corporation, Pattison Food Group Ltd., DENSO, Lockheed Martin, Forschungszentrum Jülich, University of Southern California, and Los Alamos National Laboratory.

Forward-Looking Statements

This press release contains forward-looking statements within the meaning of the Private Securities Litigation Reform Act of 1995, which statements are based on beliefs and assumptions and on information currently available. In some cases, you can identify forward-looking statements by the following words: “may,” “will,” “could,” “would,” “should,” “expect,” “intend,” “plan,” “anticipate,” “believe,” “estimate,” “predict,” “project,” “potential,” “continue,” “ongoing,” or the negative of these terms or other comparable terminology, although not all forward-looking statements contain these words. These statements involve risks, uncertainties, and other factors that may cause actual results, levels of activity, performance, or achievements to be materially different from the information expressed or implied by these forward-looking statements. We caution you that these statements are based on a combination of facts and factors currently known by us and our projections of the future, which are subject to a number of risks. Forward-looking statements in this press release include, but are not limited to, statements regarding the impact of the results of this study; the company’s Advantage2™ experimental prototype; and the potential for future problem-solving using quantum annealing. We cannot assure you that the forward-looking statements in this press release will prove to be accurate. These forward-looking statements are subject to a number of risks and uncertainties, including, among others, various factors beyond management’s control, including general economic conditions and other risks, our ability to expand our customer base and the customer adoption of our solutions, and the uncertainties and factors set forth in the sections entitled “Risk Factors” and “Cautionary Note Regarding Forward-Looking Statements” in D-Wave Quantum Inc.’s Form S-4 Registration Statement, as amended, previously filed with the Securities and Exchange Commission, as well as factors associated with companies, such as D-Wave, that are engaged in the business of quantum computing, including anticipated trends, growth rates, and challenges in those businesses and in the markets in which they operate; the outcome of any legal proceedings that may be instituted against us; risks related to the performance of our business and the timing of expected business or financial milestones; unanticipated technological or project development challenges, including with respect to the cost and or timing thereof; the performance of the our products; the effects of competition on our business; the risk that we will need to raise additional capital to execute our business plan, which may not be available on acceptable terms or at all; the risk that we may never achieve or sustain profitability; the risk that we are unable to secure or protect our intellectual property; volatility in the price of our securities; and the risk that our securities will not maintain the listing on the NYSE. Furthermore, if the forward-looking statements contained in this press release prove to be inaccurate, the inaccuracy may be material. In addition, you are cautioned that past performance may not be indicative of future results. In light of the significant uncertainties in these forward-looking statements, you should not place undue reliance on these statements in making an investment decision or regard these statements as a representation or warranty by any person we will achieve our objectives and plans in any specified time frame, or at all. The forward-looking statements in this press release represent our views as of the date of this press release. We anticipate that subsequent events and developments will cause our views to change. However, while we may elect to update these forward-looking statements at some point in the future, we have no current intention of doing so except to the extent required by applicable law. You should, therefore, not rely on these forward-looking statements as representing our views as of any date subsequent to the date of this press release.

Here’s a link to and a citation for the paper,

Quantum critical dynamics in a 5,000-qubit programmable spin glass by Andrew D. King, Jack Raymond, Trevor Lanting, Richard Harris, Alex Zucca, Fabio Altomare, Andrew J. Berkley, Kelly Boothby, Sara Ejtemaee, Colin Enderud, Emile Hoskinson, Shuiyuan Huang, Eric Ladizinsky, Allison J. R. MacDonald, Gaelen Marsden, Reza Molavi, Travis Oh, Gabriel Poulin-Lamarre, Mauricio Reis, Chris Rich, Yuki Sato, Nicholas Tsai, Mark Volkmann, Jed D. Whittaker, Jason Yao, Anders W. Sandvik & Mohammad H. Amin. Nature volume 617, pages 61–66 (2023) DOI: https://doi.org/10.1038/s41586-023-05867-2 Published: 19 April 2023 Issue Date: 04 May 2023

This paper is behind a paywall but there is an open access version on the arxiv website which means that it has had some peer review but may differ from the version in Nature.

Living photovoltaics with carbon nanotubes (CNTs)?

A September 12, 2022 news item on phys.org has an interesting lede,

“We put nanotubes inside of bacteria,” says Professor Ardemis Boghossian at EPFL’s School of Basic Sciences. “That doesn’t sound very exciting on the surface, but it’s actually a big deal. Researchers have been putting nanotubes in mammalian cells that use mechanisms like endocytosis, that are specific to those kinds of cells. Bacteria, on the other hand, don’t have these mechanisms and face additional challenges in getting particles through their tough exterior. Despite these barriers, we’ve managed to do it, and this has very exciting implications in terms of applications.”

A September 16, 2022 Ecole Polytechnique Fédérale de Lausanne (EPFL) press release (also on EurekAlert but published September 12, 2022), which originated the news item, goes on to describe this work in the field of ‘nanobionics,

Boghossian’s research focuses on interfacing artificial nanomaterials with biological constructs, including living cells. The resulting “nanobionic” technologies combine the advantages of both the living and non-living worlds. For years, her group has worked on the nanomaterial applications of single-walled carbon nanotubes (SWCNTs), tubes of carbon atoms with fascinating mechanical and optical properties.

These properties make SWCNTs [single-walled carbon nanotubes] ideal for many novel applications in the field of nanobiotechnology. For example, SWCNTs have been placed inside mammalian cells to monitor their metabolisms using near-infrared imaging. The insertion of SWCNTs in mammalian cells has also led to new technologies for delivering therapeutic drugs to their intracellular targets, while in plant cells they have been used for genome editing. SWCNTs have also been implanted in living mice to demonstrate their ability to image biological tissue deep inside the body.

Fluorescent nanotubes in bacteria: A first

In an article published in Nature Nanotechnology, Boghossian’s group with their international colleagues were able to “convince” bacteria to spontaneously take up SWCNTs by “decorating” them with positively charged proteins that are attracted by the negative charge of the bacteria’s outer membrane. The two types of bacteria explored in the study, Synechocystis and Nostoc, belong to the Cyanobacteria phylum, an enormous group of bacteria that get their energy through photosynthesis – like plants. They are also “Gram-negative”, which means that their cell wall is thin, and they have an additional outer membrane that “Gram-positive” bacteria lack.

The researchers observed that the cyanobacteria internalized SWCNTs through a passive, length-dependent and selective process. This process allowed the SWCNTs to spontaneously penetrate the cell walls of both the unicellular Synechocystis and the long, snake-like, multicellular Nostoc.

Following this success, the team wanted to see if the nanotubes can be used to image cyanobacteria – as is the case with mammalian cells. “We built a first-of-its-kind custom setup that allowed us to image the special near-infrared fluorescence we get from our nanotubes inside the bacteria,” says Boghossian.

Alessandra Antonucci, a former PhD student at Boghossian’s lab adds: “When the nanotubes are inside the bacteria, you could very clearly see them, even though the bacteria emit their own light. This is because the wavelengths of the nanotubes are far in the red, the near-infrared. You get a very clear and stable signal from the nanotubes that you can’t get from any other nanoparticle sensor. We’re excited because we can now use the nanotubes to see what is going on inside of cells that have been difficult to image using more traditional particles or proteins. The nanotubes give off a light that no natural living material gives off, not at these wavelengths, and that makes the nanotubes really stand out in these cells.”

“Inherited nanobionics”

The scientists were able to track the growth and division of the cells by monitoring the bacteria in real-time. Their findings revealed that the SWCNTs were being shared by the daughter cells of the dividing microbe.  “When the bacteria divide, the daughter cells inherent the nanotubes along with the properties of the nanotubes,” says Boghossian. “We call this ‘inherited nanobionics.’ It’s like having an artificial limb that gives you capabilities beyond what you can achieve naturally. And now imagine that your children can inherit its properties from you when they are born. Not only did we impart the bacteria with this artificial behavior, but this behavior is also inherited by their descendants. It’s our first demonstration of inherited nanobionics.”

Living photovoltaics

“Another interesting aspect is when we put the nanotubes inside the bacteria, the bacteria show a significant enhancement in the electricity it produces when it is illuminated by light,” says Melania Reggente, a postdoc with Boghossian’s group. “And our lab is now working towards the idea of using these nanobionic bacteria in a living photovoltaic.”

“Living” photovoltaics are biological energy-producing devices that use photosynthetic microorganisms. Although still in the early stages of development, these devices represent a real solution to our ongoing energy crisis and efforts against climate change.

“There’s a dirty secret in photovoltaic community,” says Boghossian. “It is green energy, but the carbon footprint is really high; a lot of CO2 is released just to make most standard photovoltaics. But what’s nice about photosynthesis is not only does it harness solar energy, but it also has a negative carbon footprint. Instead of releasing CO2, it absorbs it. So it solves two problems at once: solar energy conversion and CO2 sequestration. And these solar cells are alive. You do not need a factory to build each individual bacterial cell; these bacteria are self-replicating. They automatically take up CO2 to produce more of themselves.  This is a material scientist’s dream.”

Boghossian envisions a living photovoltaic device based on cyanobacteria that have automated control over electricity production that does not rely on the addition of foreign particles. “In terms of implementation, the bottleneck now is the cost and environmental effects of putting nanotubes inside of cyanobacteria on a large scale.”

With an eye towards large-scale implementation, Boghossian and her team are looking to synthetic biology for answers: “Our lab is now working towards bioengineering cyanobacteria that can produce electricity without the need for nanoparticle additives. Advancements in synthetic biology allow us to reprogram these cells to behave in totally artificial ways. We can engineer them so that producing electricity is literally in their DNA.”

Other contributors

University of Freiburg
Swiss Center for Electronics and Microtechnology
University of Salento
Sapienza University of Rome

Here’s a link to and a citation for the paper,

Carbon nanotube uptake in cyanobacteria for near-infrared imaging and enhanced bioelectricity generation in living photovoltaics by Alessandra Antonucci, Melania Reggente, Charlotte Roullier, Alice J. Gillen, Nils Schuergers, Vitalijs Zubkovs, Benjamin P. Lambert, Mohammed Mouhib, Elisabetta Carata, Luciana Dini & Ardemis A. Boghossian. Nature Nanotechnology (2022) DOI: https://doi.org/10.1038/s41565-022-01198-x Published: 12 September 2022

This paper is behind a paywall.

Nanosensors use AI to explore the biomolecular world

EPFL scientists have developed AI-powered nanosensors that let researchers track various kinds of biological molecules without disturbing them. Courtesy: École polytechnique fédérale de Lausanne (EPFL)

If you look at the big orange dot (representing the nanosensors?), you’ll see those purplish/fuschia objects resemble musical notes (biological molecules?). I think that brainlike object to the left and in light blue is the artificial intelligence (AI) component. (If anyone wants to correct my guesses or identify the bits I can’t, please feel free to add to the Comments for this blog.)

Getting back to my topic, keep the ‘musical notes’ in mind as you read about some of the latest research from l’École polytechnique fédérale de Lausanne (EPFL) in an April 7, 2021 news item on Nanowerk,

The tiny world of biomolecules is rich in fascinating interactions between a plethora of different agents such as intricate nanomachines (proteins), shape-shifting vessels (lipid complexes), chains of vital information (DNA) and energy fuel (carbohydrates). Yet the ways in which biomolecules meet and interact to define the symphony of life is exceedingly complex.

Scientists at the Bionanophotonic Systems Laboratory in EPFL’s School of Engineering have now developed a new biosensor that can be used to observe all major biomolecule classes of the nanoworld without disturbing them. Their innovative technique uses nanotechnology, metasurfaces, infrared light and artificial intelligence.

To each molecule its own melody

In this nano-sized symphony, perfect orchestration makes physiological wonders such as vision and taste possible, while slight dissonances can amplify into horrendous cacophonies leading to pathologies such as cancer and neurodegeneration.

An April 7, 2021 EPFL press release, which originated the news item, provides more detail,

“Tuning into this tiny world and being able to differentiate between proteins, lipids, nucleic acids and carbohydrates without disturbing their interactions is of fundamental importance for understanding life processes and disease mechanisms,” says Hatice Altug, the head of the Bionanophotonic Systems Laboratory. 

Light, and more specifically infrared light, is at the core of the biosensor developed by Altug’s team. Humans cannot see infrared light, which is beyond the visible light spectrum that ranges from blue to red. However, we can feel it in the form of heat in our bodies, as our molecules vibrate under the infrared light excitation.

Molecules consist of atoms bonded to each other and – depending on the mass of the atoms and the arrangement and stiffness of their bonds – vibrate at specific frequencies. This is similar to the strings on a musical instrument that vibrate at specific frequencies depending on their length. These resonant frequencies are molecule-specific, and they mostly occur in the infrared frequency range of the electromagnetic spectrum. 

“If you imagine audio frequencies instead of infrared frequencies, it’s as if each molecule has its own characteristic melody,” says Aurélian John-Herpin, a doctoral assistant at Altug’s lab and the first author of the publication. “However, tuning into these melodies is very challenging because without amplification, they are mere whispers in a sea of sounds. To make matters worse, their melodies can present very similar motifs making it hard to tell them apart.” 

Metasurfaces and artificial intelligence

The scientists solved these two issues using metasurfaces and AI. Metasurfaces are man-made materials with outstanding light manipulation capabilities at the nano scale, thereby enabling functions beyond what is otherwise seen in nature. Here, their precisely engineered meta-atoms made out of gold nanorods act like amplifiers of light-matter interactions by tapping into the plasmonic excitations resulting from the collective oscillations of free electrons in metals. “In our analogy, these enhanced interactions make the whispered molecule melodies more audible,” says John-Herpin.

AI is a powerful tool that can be fed with more data than humans can handle in the same amount of time and that can quickly develop the ability to recognize complex patterns from the data. John-Herpin explains, “AI can be imagined as a complete beginner musician who listens to the different amplified melodies and develops a perfect ear after just a few minutes and can tell the melodies apart, even when they are played together – like in an orchestra featuring many instruments simultaneously.” 

The first biosensor of its kind

When the scientists’ infrared metasurfaces are augmented with AI, the new sensor can be used to analyze biological assays featuring multiple analytes simultaneously from the major biomolecule classes and resolving their dynamic interactions. 

“We looked in particular at lipid vesicle-based nanoparticles and monitored their breakage through the insertion of a toxin peptide and the subsequent release of vesicle cargos of nucleotides and carbohydrates, as well as the formation of supported lipid bilayer patches on the metasurface,” says Altug.

This pioneering AI-powered, metasurface-based biosensor will open up exciting perspectives for studying and unraveling inherently complex biological processes, such as intercellular communication via exosomesand the interaction of nucleic acids and carbohydrates with proteins in gene regulation and neurodegeneration. 

“We imagine that our technology will have applications in the fields of biology, bioanalytics and pharmacology – from fundamental research and disease diagnostics to drug development,” says Altug. 

Here’s a link to and a citation for the paper,

Infrared Metasurface Augmented by Deep Learning for Monitoring Dynamics between All Major Classes of Biomolecules by Aurelian John‐Herpin, Deepthy Kavungal. Lea von Mücke, Hatice Altug. Advanced Materials Volume 33, Issue 14 April 8, 2021 2006054 DOI: https://doi.org/10.1002/adma.202006054 First published: 22 February 2021

This paper is open access.

Making carbon capture more efficient and cheaper with graphene filters

Years ago someone asked me if there was any nanotechnology research into carbon capture. I couldn’t answer the question at the time but since then I’ve been on the lookout for more on the topic. So, I’m happy to add this February 25, 2021 news item on Nanowerk to my growing number of carbon capture posts (Note: A link has been removed),

One of the main culprits of global warming is the vast amount of carbon dioxide pumped out into the atmosphere mostly from burning fossil fuels and the production of steel and cement. In response, scientists have been trying out a process that can sequester waste carbon dioxide, transporting it into a storage site, and then depositing it at a place where it cannot enter the atmosphere.

The problem is that capturing carbon from power plants and industrial emissions isn’t very cost-effective. The main reason is that waste carbon dioxide isn’t emitted pure, but is mixed with nitrogen and other gases, and extracting it from industrial emissions requires extra energy consumption – meaning a pricier bill.

Scientists have been trying to develop an energy-efficient carbon dioxide-filter. Referred to as a “membrane”, this technology can extract carbon dioxide out of the gas mix, which can then be either stored or converted into useful chemicals. “However, the performance of current carbon dioxide filters has been limited by the fundamental properties of currently available materials,” explains Professor Kumar Varoon Agrawal at EPFL’s School of Basic Sciences (EPFL Valais Wallis).

Now, Agrawal has led a team of chemical engineers to develop the world’s thinnest filter from graphene, the world-famous “wonder material” that won the Physics Nobel in 2010. But the graphene filter isn’t just the thinnest in the world, it can also separate carbon dioxide from a mix of gases such as those coming out of industrial emissions and do so with an efficiency and speed that surpasses most current filters.

A March 3, 2021 Ecole Polytechnique Fédérale de Lausanne (EPFL) press release (also on EurekAlert but published February 25, 2021), which originated the news item, delves further into the topic,

“Our approach was simple,” says Agrawal. “We made carbon dioxide-sized holes in graphene, which allowed carbon dioxide to flow through while blocking other gases such as nitrogen, which are larger than carbon dioxide.” The result is a record-high carbon dioxide-capture performance.

For comparison, current filters are required to exceed 1000 gas permeation units (GPUs), while their carbon-capturing specificity, referred to as their “carbon dioxide/nitrogen separation factor” must be above 20. The membranes that the EPFL scientists developed show more than ten-fold higher carbon dioxide permeance at 11,800 GPUs, while their separation factor stands at 22.5.

“We estimate that this technology will drop the cost of carbon capture close to $30 per ton of carbon dioxide, in contrast to commercial processes where the cost is two-to-four time higher,” says Agrawal. His team is now working on scaling up the process by developing a pilot plant demonstrator to capture 10 kg carbon dioxide per day, in a project funded by the Swiss government and Swiss industry.

Here’s a link to and a citation for the paper,

Millisecond lattice gasification for high-density CO2– and O2-sieving nanopores in single-layer graphene by Shiqi Huang, Shaoxian Li, Luis Francisco Villalobos, Mostapha Dakhchoune, Marina Micari, Deepu J. Babu, Mohammad Tohidi Vahdat, Mounir Mensi, Emad Oveisi and Kumar Varoon Agrawal. Science Advances 24 Feb 2021: Vol. 7, no. 9, eabf0116 DOI: 10.1126/sciadv.abf0116

This paper appears to be open access.

Exotic magnetism: a quantum simulation from D-Wave Sytems

Vancouver (Canada) area company, D-Wave Systems is trumpeting itself (with good reason) again. This 2021 ‘milestone’ achievement builds on work from 2018 (see my August 23, 2018 posting for the earlier work). For me, the big excitement was finding the best explanation for quantum annealing and D-Wave’s quantum computers that I’ve seen yet (that explanation and a link to more is at the end of this posting).

A February 18, 2021 news item on phys.org announces the latest achievement,

D-Wave Systems Inc. today [February 18, 2021] published a milestone study in collaboration with scientists at Google, demonstrating a computational performance advantage, increasing with both simulation size and problem hardness, to over 3 million times that of corresponding classical methods. Notably, this work was achieved on a practical application with real-world implications, simulating the topological phenomena behind the 2016 Nobel Prize in Physics. This performance advantage, exhibited in a complex quantum simulation of materials, is a meaningful step in the journey toward applications advantage in quantum computing.

A February 18, 2021 D-Wave Systems press release (also on EurekAlert), which originated the news item, describes the work in more detail,

The work by scientists at D-Wave and Google also demonstrates that quantum effects can be harnessed to provide a computational advantage in D-Wave processors, at problem scale that requires thousands of qubits. Recent experiments performed on multiple D-Wave processors represent by far the largest quantum simulations carried out by existing quantum computers to date.

The paper, entitled “Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets”, was published in the journal Nature Communications (DOI 10.1038/s41467-021-20901-5, February 18, 2021). D-Wave researchers programmed the D-Wave 2000Q™ system to model a two-dimensional frustrated quantum magnet using artificial spins. The behavior of the magnet was described by the Nobel-prize winning work of theoretical physicists Vadim Berezinskii, J. Michael Kosterlitz and David Thouless. They predicted a new state of matter in the 1970s characterized by nontrivial topological properties. This new research is a continuation of previous breakthrough work published by D-Wave’s team in a 2018 Nature paper entitled “Observation of topological phenomena in a programmable lattice of 1,800 qubits” (Vol. 560, Issue 7719, August 22, 2018). In this latest paper, researchers from D-Wave, alongside contributors from Google, utilize D-Wave’s lower noise processor to achieve superior performance and glean insights into the dynamics of the processor never observed before.

“This work is the clearest evidence yet that quantum effects provide a computational advantage in D-Wave processors,” said Dr. Andrew King, principal investigator for this work at D-Wave. “Tying the magnet up into a topological knot and watching it escape has given us the first detailed look at dynamics that are normally too fast to observe. What we see is a huge benefit in absolute terms, with the scaling advantage in temperature and size that we would hope for. This simulation is a real problem that scientists have already attacked using the algorithms we compared against, marking a significant milestone and an important foundation for future development. This wouldn’t have been possible today without D-Wave’s lower noise processor.”

“The search for quantum advantage in computations is becoming increasingly lively because there are special problems where genuine progress is being made. These problems may appear somewhat contrived even to physicists, but in this paper from a collaboration between D-Wave Systems, Google, and Simon Fraser University [SFU], it appears that there is an advantage for quantum annealing using a special purpose processor over classical simulations for the more ‘practical’ problem of finding the equilibrium state of a particular quantum magnet,” said Prof. Dr. Gabriel Aeppli, professor of physics at ETH Zürich and EPF Lausanne, and head of the Photon Science Division of the Paul Scherrer Institute. “This comes as a surprise given the belief of many that quantum annealing has no intrinsic advantage over path integral Monte Carlo programs implemented on classical processors.”

“Nascent quantum technologies mature into practical tools only when they leave classical counterparts in the dust in solving real-world problems,” said Hidetoshi Nishimori, Professor, Institute of Innovative Research, Tokyo Institute of Technology. “A key step in this direction has been achieved in this paper by providing clear evidence of a scaling advantage of the quantum annealer over an impregnable classical computing competitor in simulating dynamical properties of a complex material. I send sincere applause to the team.”

“Successfully demonstrating such complex phenomena is, on its own, further proof of the programmability and flexibility of D-Wave’s quantum computer,” said D-Wave CEO Alan Baratz. “But perhaps even more important is the fact that this was not demonstrated on a synthetic or ‘trick’ problem. This was achieved on a real problem in physics against an industry-standard tool for simulation–a demonstration of the practical value of the D-Wave processor. We must always be doing two things: furthering the science and increasing the performance of our systems and technologies to help customers develop applications with real-world business value. This kind of scientific breakthrough from our team is in line with that mission and speaks to the emerging value that it’s possible to derive from quantum computing today.”

The scientific achievements presented in Nature Communications further underpin D-Wave’s ongoing work with world-class customers to develop over 250 early quantum computing applications, with a number piloting in production applications, in diverse industries such as manufacturing, logistics, pharmaceutical, life sciences, retail and financial services. In September 2020, D-Wave brought its next-generation Advantage™ quantum system to market via the Leap™ quantum cloud service. The system includes more than 5,000 qubits and 15-way qubit connectivity, as well as an expanded hybrid solver service capable of running business problems with up to one million variables. The combination of Advantage’s computing power and scale with the hybrid solver service gives businesses the ability to run performant, real-world quantum applications for the first time.

That last paragraph seems more sales pitch than research oriented. It’s not unexpected in a company’s press release but I was surprised that the editors at EurekAlert didn’t remove it.

Here’s a link to and a citation for the latest paper,

Scaling advantage over path-integral Monte Carlo in quantum simulation of geometrically frustrated magnets by Andrew D. King, Jack Raymond, Trevor Lanting, Sergei V. Isakov, Masoud Mohseni, Gabriel Poulin-Lamarre, Sara Ejtemaee, William Bernoudy, Isil Ozfidan, Anatoly Yu. Smirnov, Mauricio Reis, Fabio Altomare, Michael Babcock, Catia Baron, Andrew J. Berkley, Kelly Boothby, Paul I. Bunyk, Holly Christiani, Colin Enderud, Bram Evert, Richard Harris, Emile Hoskinson, Shuiyuan Huang, Kais Jooya, Ali Khodabandelou, Nicolas Ladizinsky, Ryan Li, P. Aaron Lott, Allison J. R. MacDonald, Danica Marsden, Gaelen Marsden, Teresa Medina, Reza Molavi, Richard Neufeld, Mana Norouzpour, Travis Oh, Igor Pavlov, Ilya Perminov, Thomas Prescott, Chris Rich, Yuki Sato, Benjamin Sheldan, George Sterling, Loren J. Swenson, Nicholas Tsai, Mark H. Volkmann, Jed D. Whittaker, Warren Wilkinson, Jason Yao, Hartmut Neven, Jeremy P. Hilton, Eric Ladizinsky, Mark W. Johnson, Mohammad H. Amin. Nature Communications volume 12, Article number: 1113 (2021) DOI: https://doi.org/10.1038/s41467-021-20901-5 Published: 18 February 2021

This paper is open access.

Quantum annealing and more

Dr. Andrew King, one of the D-Wave researchers, has written a February 18, 2021 article on Medium explaining some of the work. I’ve excerpted one of King’s points,

Insight #1: We observed what actually goes on under the hood in the processor for the first time

Quantum annealing — the approach adopted by D-Wave from the beginning — involves setting up a simple but purely quantum initial state, and gradually reducing the “quantumness” until the system is purely classical. This takes on the order of a microsecond. If you do it right, the classical system represents a hard (NP-complete) computational problem, and the state has evolved to an optimal, or at least near-optimal, solution to that problem.

What happens at the beginning and end of the computation are about as simple as quantum computing gets. But the action in the middle is hard to get a handle on, both theoretically and experimentally. That’s one reason these experiments are so important: they provide high-fidelity measurements of the physical processes at the core of quantum annealing. Our 2018 Nature article introduced the same simulation, but without measuring computation time. To benchmark the experiment this time around, we needed lower-noise hardware (in this case, we used the D-Wave 2000Q lower noise quantum computer), and we needed, strangely, to slow the simulation down. Since the quantum simulation happens so fast, we actually had to make things harder. And we had to find a way to slow down both quantum and classical simulation in an equitable way. The solution? Topological obstruction.

If you have time and the inclination, I encourage you to read King’s piece.

Wormlike communication at the nanoscale

These days I need a little joy and these two researchers seem happy to share,

Prof. Dirk Grundler and doctoral assistant Sho Watanabe with a broadband spin-wave spectroscopy set up. Credit: EPFL / Alain Herzog

A July 15, 2020 news item on phys.org announces the development that so delights these researchers,

Researchers at EPFL [École polytechnique fédérale de Lausanne; Switzerland] have shown that electromagnetic waves coupled to precisely engineered structures known as artificial ferromagnetic quasicrystals allow for more efficient information transmission and processing at the nanoscale. Their research also represents the first practical demonstration of Conway worms, a theoretical concept for the description of quasicrystals.

A July 15, 2020 EPFL press release, which originated the news item, explains further,

High-frequency electromagnetic waves are used to transmit and process information in microelectronic devices such as smartphones. It’s already appreciated that these waves can be compressed using magnetic oscillations known as spin waves or magnons. This compression could pave the way for the design of nanoscale, multifunctional microwave devices with a considerably reduced footprint. But first, scientists need to gain a better understanding of spin waves – or precisely how magnons behave and propagate in different structures.

Learning more about aperiodic structures

In a study conducted by the doctoral assistant Sho Watanabe, postdoctoral researcher Dr. Vinayak Bhat, and further team members, the scientists from EPFL’s Laboratory of Nanoscale Magnetic Materials and Magnonics (LMGN) examined how electromagnetic waves propagate, and how they could be manipulated, in precisely engineered nanostructures known as artificial ferromagnetic quasicrystals. The quasicrystals have a unique property: their structure is aperiodic, meaning that their constituent atoms or tailor-made elements do not follow a regular, repeating pattern but are still arranged deterministically. Although this characteristic makes materials especially useful for the design of everyday and high-tech devices, it remains poorly understood.

Faster, easier transmission of information

The LMGN team found that, under controlled conditions, a single electromagnetic wave coupled to an artificial quasicrystal splits into several spin waves, which then propagate within the structure. Each of these spin waves represents a different phase of the original electromagnetic wave, carrying different information. “It’s a very interesting discovery, because existing information-transmission methods follow the same principle,” says Dirk Grundler, an associate professor at EPFL’s School of Engineering (STI). “Except you need an extra device, a multiplexer, to split the input signal because – unlike in our study – it doesn’t divide on its own.”

Grundler also explains that, in conventional systems, the information contained in each wave can only be read at different frequencies – another inconvenience that the EPFL team overcame in their study. “In our two-dimensional quasicrystals, all the waves can be read at the same frequency,” he adds. The findings have been published in the journal Advanced Functional Materials.

Waves that spread like worms

The researchers also observed that, rather than propagating randomly, the waves often moved like so-called Conway worms, named after a well-known mathematician John Horton Conway who also developed a model to describe the behavior and feeding patterns of prehistoric worms. Conway discovered that, within two-dimensional quasicrystals, constituent elements arrange like meandering worms following a Fibonacci sequence. Thereby they form selected one-dimensional quasicrystals. “Our study represents the first practical demonstration of this theoretical concept, proving that the sequences induce interesting functional properties of waves in a quasicrystal,” says Grundler.

Take a look at that last paragraph. A mathematician develops a model for how prehistoric worms may have moved and applies it, theoretically, to 2D quasicrystals which these researchers believe they’ve observed in the laboratory and they believe this may have an impact on our future electronic devices. Sometimes I sit at home in wonder.

Here’s a link to and a citation for the paper,

Direct Observation of Worm‐Like Nanochannels and Emergent Magnon Motifs in Artificial Ferromagnetic Quasicrystals by Sho Watanabe, Vinayak S. Bhat, Korbinian Baumgaert, Dirk Grundler. Advanced Functional Materials DOI: https://doi.org/10.1002/adfm.202001388 First published: 15 July 2020

This is an open access paper.

The mention of quasicrystals reminded me of Daniel Schechtman who received the Nobel Prize for Chemistry in 2011 and who was mentioned in a December 24, 2013 posting here,

“I suggested earlier that this achievement has a fabulous quality and the Daniel Schechtman backstory is the reason. The winner of the 2011 Nobel Prize for Chemistry, Schechtman was reviled for years [emphasis mine] within his scientific community as Ian Sample notes in his Oct. 5, 2011 article on the announcement of Schechtman’s Nobel win written for the Guardian newspaper (Note: A link has been removed),

A scientist whose work was so controversial he was ridiculed and asked to leave his research group has won the Nobel Prize in Chemistry.

Daniel Shechtman, 70, a researcher at Technion-Israel Institute of Technology in Haifa, received the award for discovering seemingly impossible crystal structures in frozen gobbets of metal that resembled the beautiful patterns seen in Islamic mosaics.

Images of the metals showed their atoms were arranged in a way that broke well-establised rules of how crystals formed, a finding that fundamentally altered how chemists view solid matter.

You may want to click on the Guardian link to the full story about Schechtman and his quasicrystals. As for my December 24, 2013 posting, that features news of the creation of the first single-element quasicrystal in a laboratory along with an excerpt of the Schechtman story (scroll down about 50% of the way).

Feeling with a bionic finger

From what I understand one of the most difficult aspects of an amputation is the loss of touch, so, bravo to the engineers. From a March 8, 2016 news item on ScienceDaily,

An amputee was able to feel smoothness and roughness in real-time with an artificial fingertip that was surgically connected to nerves in his upper arm. Moreover, the nerves of non-amputees can also be stimulated to feel roughness, without the need of surgery, meaning that prosthetic touch for amputees can now be developed and safely tested on intact individuals.

The technology to deliver this sophisticated tactile information was developed by Silvestro Micera and his team at EPFL (Ecole polytechnique fédérale de Lausanne) and SSSA (Scuola Superiore Sant’Anna) together with Calogero Oddo and his team at SSSA. The results, published today in eLife, provide new and accelerated avenues for developing bionic prostheses, enhanced with sensory feedback.

A March 8, 2016 EPFL press release (also on EurekAlert), which originated the news item, provides more information about Sorenson’s experience and about the other tests the research team performed,

“The stimulation felt almost like what I would feel with my hand,” says amputee Dennis Aabo Sørensen about the artificial fingertip connected to his stump. He continues, “I still feel my missing hand, it is always clenched in a fist. I felt the texture sensations at the tip of the index finger of my phantom hand.”

Sørensen is the first person in the world to recognize texture using a bionic fingertip connected to electrodes that were surgically implanted above his stump.

Nerves in Sørensen’s arm were wired to an artificial fingertip equipped with sensors. A machine controlled the movement of the fingertip over different pieces of plastic engraved with different patterns, smooth or rough. As the fingertip moved across the textured plastic, the sensors generated an electrical signal. This signal was translated into a series of electrical spikes, imitating the language of the nervous system, then delivered to the nerves.

Sørensen could distinguish between rough and smooth surfaces 96% of the time.

In a previous study, Sorensen’s implants were connected to a sensory-enhanced prosthetic hand that allowed him to recognize shape and softness. In this new publication about texture in the journal eLife, the bionic fingertip attains a superior level of touch resolution.

Simulating touch in non-amputees

This same experiment testing coarseness was performed on non-amputees, without the need of surgery. The tactile information was delivered through fine, needles that were temporarily attached to the arm’s median nerve through the skin. The non-amputees were able to distinguish roughness in textures 77% of the time.

But does this information about touch from the bionic fingertip really resemble the feeling of touch from a real finger? The scientists tested this by comparing brain-wave activity of the non-amputees, once with the artificial fingertip and then with their own finger. The brain scans collected by an EEG cap on the subject’s head revealed that activated regions in the brain were analogous.

The research demonstrates that the needles relay the information about texture in much the same way as the implanted electrodes, giving scientists new protocols to accelerate for improving touch resolution in prosthetics.

“This study merges fundamental sciences and applied engineering: it provides additional evidence that research in neuroprosthetics can contribute to the neuroscience debate, specifically about the neuronal mechanisms of the human sense of touch,” says Calogero Oddo of the BioRobotics Institute of SSSA. “It will also be translated to other applications such as artificial touch in robotics for surgery, rescue, and manufacturing.”

Here’s a link to and a citation for the paper,

Intraneural stimulation elicits discrimination of textural features by artificial fingertip in intact and amputee humans by Calogero Maria Oddo, Stanisa Raspopovic, Fiorenzo Artoni, Alberto Mazzoni, Giacomo Spigler, Francesco Petrini, Federica Giambattistelli, Fabrizio Vecchio, Francesca Miraglia, Loredana Zollo, Giovanni Di Pino, Domenico Camboni, Maria Chiara Carrozza, Eugenio Guglielmelli, Paolo Maria Rossini, Ugo Faraguna, Silvestro Micera. eLife, 2016; 5 DOI: 10.7554/eLife.09148 Published March 8, 2016

This paper appears to be open access.